sustAInability - Advanced topics in sustainability and artificial intelligence

150h workload, including

• self-study
• weekly seminar sessions

This module is open to all students enrolled in a Master’s program at the Technical University of Munich (TUM) or at the Hochschule München University of Applied Sciences (HM); it is thus designed as an interdisciplinary module which brings together a range of academic perspectives. No specific prior knowledge is required; however, its project-based character requires high levels of intrinsic motivation and the willingness to actively participate in project-based learning. Students with a technological background are as welcome as students from social sciences, economics, design, or humanities.

After successful participation in this module, students are able to

• define the concept of sustainability
• describe the term artificial intelligence (AI) and name technologies using AI
• explain in their own words the main ideas of sustainable AI
• explain in their own words the main ideas of AI for sustainability
• analyze and discuss current research in the fields of sustainable AI as well as AI for sustainability
• to develop and present solutions for real-world problems based on AI and sustainable development goals
• to systematically plan and implement their own projects within this module Students will be able to gain further competences:
• language and communication skills: Working and learning in a diverse, international, and interdisciplinary group of students
• presentation skills: in-class presentations during the seminars and during the workshop week

Sustainability as a central, political, and societal goal, can serve as an orientation framework for the responsible development of AI technologies as well as a compass for their use. For this to succeed, both sociological and technical perspectives are necessary. For universities - but also for other institutions in politics, society, and business - this means that disciplinary boundaries must increasingly be broken down and interdisciplinary teaching and learning formats should be created. One such format is "sustAInability" during which students approach AI from various sustainability perspectives.

Introduction of the topics sustainability and AI

• definition of sustainability and its three dimensions: environmental, economic, and social
• definition of AI and AI-based technologies

Sustainability of AI:

• research on and examples for sustainable AI in all three dimensions
• energy reduction and reduction of CO2-emissions while using AI
• ethical justice in data sources/training data

AI for Sustainability

• research on and examples for AI for sustainability in all three dimensions
• existing tools and technologies for climate protection and biodiversity
• challenges and bias

Interdisciplinary project in the context of sustainability and AI

• students will apply their understanding of the complex interplay between sustainability and AI
• interdisciplinary teams to develop AI-based concepts and approaches addressing key sustainability challenges. The project-methods are not limited to software-based applications.

Media:

• research papers, blogposts, News articles
• powerpoints
• podcasts
• videos

Methods:

• self-study
• futurizing workshop
• just-in-time-teaching
• prototyping
• design thinking
• group work

• van Wynsberghe, A. (2021). Sustainable AI: AI for sustainability and the sustainability of AI. AI and Ethics, https://www.researchgate.net/publication/349639276_Sustainable_AI_AI_for_sustainability_and_the_sustainability_of_AI

• Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., Felländer, A., Langhans, S. D.,Tegmark, M., and Nerini, F. F. (2020). The role of artifcial intelligence in achieving the sustainable development goals. Nature Communications, https://www.nature.com/articles/s41467-019-14108-y

• more reading materials will be provided in the self-study materials during the course